Quantum Fast Algorithm Computational Intelligence PT I:SW/HW Smart Toolkit

A new approach to a circuit implementation design of quantum algorithm gates for quantum massive parallel fast computing implementation is presented.The main attention is focused on the development of design method of fast quantum algorithm operators as superposition,entanglement and interference which are in general time-consuming operations due to the number of products that have to be performed.SW&HW support sophisticated smart toolkit of supercomputing accelerator of quantum algorithm simulation is described.The method for performing Grover’s interference without product operations as Benchmark introduced.The background of developed information technology is the"Quantum/Soft Computing Optimizer"(QSCOptKBTM)software based on soft and quantum computational intelligence toolkit.Quantum genetic and quantum fuzzy inference algorithm gate design considered.The quantum information technology of imperfect knowledge base self-organization design of fuzzy robust controllers for the guaranteed achievement of intelligent autonomous robot the control goal in unpredicted control situations is described.

The Comparison of Current Development,Technology and Governments’Attitudes of Driverless Car at Home and Abroad

Driverless car,as a direction for future automobile development,greatly improves the efficiency and safety of the traffic system.It’s one of the most popular technical fields.In recent years,driverless car has developed rapidly.The related development is concerned by governments,businesses,consumers and stakeholders widely,and most of countries have been actively studying this technology.This paper first introduces the current development of driverless car at home and abroad.Besides,the basic technologies of driverless car are briefly analyzed.In addition,the author compares the American government’s attitudes with Chinese government’s attitudes towards driverless car.Specifically,the article makes an analysis of contents of literature and periodicals at home and abroad and policies and documents which have already been published.The analysis shows that there is no great difference between the attitudes of Chinese and American governments.Both of two governments actively support the development of driverless car.Finally,this paper expounds the development direction of the driverless car field in future by dividing into two categories through road conditions:automatic driving on expressways and automatic driving in cities.

Research and Analysis of Machine Learning Algorithm in Artificial Intelligence

This article firstly explains the concepts of artificial intelligence and algorithm separately,then determines the research status of artificial intelligence and machine learning in the background of the increasing popularity of artificial intelligence,and finally briefly describes the machine learning algorithm in the field of artificial intelligence,as well as puts forward appropriate development prospects,in order to provide theoretical reference for industry insider.

Quantum Algorithm of Imperfect KB Self-organization Pt I: Smart Control-Information-Thermodynamic Bounds

The quantum self-organization algorithm model of wise knowledge base design for intelligent fuzzy controllers with required robust level considered.Background of the model is a new model of quantum inference based on quantum genetic algorithm.Quantum genetic algorithm applied on line for the quantum correlation’s type searching between unknown solutions in quantum superposition of imperfect knowledge bases of intelligent controllers designed on soft computing.Disturbance conditions of analytical information-thermodynamic trade-off interrelations between main control quality measures(as new design laws)discussed in Part I.The smart control design with guaranteed achievement of these trade-off interrelations is main goal for quantum self-organization algorithm of imperfect KB.Sophisticated synergetic quantum information effect in Part I(autonomous robot in unpredicted control situations)and II(swarm robots with imperfect KB exchanging between“master-slaves”)introduced:a new robust smart controller on line designed from responses on unpredicted control situations of any imperfect KB applying quantum hidden information extracted from quantum correlation.Within the toolkit of classical intelligent control,the achievement of the similar synergetic information effect is impossible.Benchmarks of intelligent cognitive robotic control applications considered.

To Perform Road Signs Recognition for Autonomous Vehicles Using Cascaded Deep Learning Pipeline

Autonomous vehicle is a vehicle that can guide itself without human conduction.It is capable of sensing its environment and moving with little or no human input.This kind of vehicle has become a concrete reality and may pave the way for future systems where computers take over the art of driving.Advanced artificial intelligence control systems interpret sensory information to identify appropriate navigation paths,as well as obstacles and relevant road signs.In this paper,we introduce an intelligent road signs classifier to help autonomous vehicles to recognize and understand road signs.The road signs classifier based on an artificial intelligence technique.In particular,a deep learning model is used,Convolutional Neural Networks(CNN).CNN is a widely used Deep Learning model to solve pattern recognition problems like image classification and object detection.CNN has successfully used to solve computer vision problems because of its methodology in processing images that are similar to the human brain decision making.The evaluation of the proposed pipeline was trained and tested using two different datasets.The proposed CNNs achieved high performance in road sign classification with a validation accuracy of 99.8%and a testing accuracy of 99.6%.The proposed method can be easily implemented for real time application.

Using the CVP Traffic Detection Model at Road-Section Applies to Traffic Information Collection and Monitor—the Case Study

This paper proposes a using Cellular-Based Vehicle Probe(CVP)at road-section(RS)method to detect and setup a model for traffic flow information(info)collection and monitor.There are multiple traffic collection devices including CVP,ETC-Based Vehicle Probe(EVP),Vehicle Detector(VD),and CCTV as traffic resources to serve as road condition info for predicting the traffic jam problem,monitor and control.The main project has been applied at Tai#2 Ghee-Jing roadway connects to Wan-Li section as a trial field on fiscal year of 2017-2018.This paper proposes a man-flow turning into traffic-flow with Long-Short Time Memory(LTSM)from recurrent neural network(RNN)model.We also provide a model verification and validation methodology with RNN for cross verification of system performance.

A Novel Dataset For Intelligent Indoor Object Detection Systems

Indoor Scene understanding and indoor objects detection is a complex high-level task for automated systems applied to natural environments.Indeed,such a task requires huge annotated indoor images to train and test intelligent computer vision applications.One of the challenging questions is to adopt and to enhance technologies to assist indoor navigation for visually impaired people(VIP)and thus improve their daily life quality.This paper presents a new labeled indoor object dataset elaborated with a goal of indoor object detection(useful for indoor localization and navigation tasks).This dataset consists of 8000 indoor images containing 16 different indoor landmark objects and classes.The originality of the annotations comes from two new facts taken into account:(1)the spatial relationships between objects present in the scene and(2)actions possible to apply to those objects(relationships between VIP and an object).This collected dataset presents many specifications and strengths as it presents various data under various lighting conditions and complex image background to ensure more robustness when training and testing objects detectors.The proposed dataset,ready for use,provides 16 vital indoor object classes in order to contribute for indoor assistance navigation for VIP.

Probabilistic Rationale of Actions for Artificial Intelligence Systems Operating in Uncertainty Conditions

The approach for probabilistic rationale of artificial intelligence systems actions is proposed.It is based on an implementation of the proposed interconnected ideas 1-7 about system analysis and optimization focused on prognostic modeling.The ideas may be applied also by using another probabilistic models which supported by software tools and can predict successfulness or risks on a level of probability distribution functions.The approach includes description of the proposed probabilistic models,optimization methods for rationale actions and incremental algorithms for solving the problems of supporting decision-making on the base of monitored data and rationale robot actions in uncertainty conditions.The approach means practically a proactive commitment to excellence in uncertainty conditions.A suitability of the proposed models and methods is demonstrated by examples which cover wide applications of artificial intelligence systems.

GFLIB:an Open Source Library for Genetic Folding Solving Optimization Problems

This paper aims at presenting GFLIB,a Genetic Folding MATLAB toolbox for supervised learning problems.In essence,the goal of GFLIB is to build a concise model of supervised learning,and a free open source MATLAB toolbox for performing classification and regression.The GFLIB is specifically designed for most of the traditionally used features,to evolve in applications of mathematical models.The toolbox suits all kinds of users;from the users who implemented GFLIB as“black box”,to advanced researchers who want to generate and test new functionalities and parameters of GF algorithm.The toolbox and its documentation are freely available for download at:https://github.com/mohabedalgani/gflib.git.

Architecture of a Commercialized Search Engine Using Mobile Agents

Shopping Search Engine(SSE)implies a unique challenge for validating distinct items available online in market place.For sellers,having a user finding relevant search results on top is very difficult.Buyers tend to click on and buy from the listings which appear first.Search engine optimization devotes that goal to influence such challenges.In current shopping search platforms,lots of irrelevant items retrieved from their indices;e.g.retrieving accessories of exact items rather than retrieving the items itself,regardless the price of item were considered or not.Also,users tend to move from shoppers to another searching for appropriate items where the time is crucial for consumers.In our proposal,we exploit the drawbacks of current shopping search engines,and the main goal of this research is to combine and merge multiple search results retrieved from some highly professional shopping sellers in the commercial market.Experimental results showed that our approach is more efficient and robust for retrieving a complete list of desired and relevant items with respect to all query space.

Development of a Novel Media-independent Communication Theology for Accessing Local&Web-based Data:Case Study with Robotic Subsystems

Realizing media independence in today’s communication system remains an open problem by and large.Information retrieval,mostly through the Internet,is becoming the most demanding feature in technological progress and this web-based data access should ideally be in user-selective form.While blind-folded access of data through the World Wide Web is quite streamlined,the counter-half of the facet,namely,seamless access of information database pertaining to a specific end-device,e.g.robotic systems,is still in a formative stage.This paradigm of access as well as systematic query-based retrieval of data,related to the physical enddevice is very crucial in designing the Internet-based network control of the same in real-time.Moreover,this control of the end-device is directly linked up to the characteristics of three coupled metrics,namely,‘multiple databases’,‘multiple servers’and‘multiple inputs’(to each server).This triad,viz.database-input-server(DIS)plays a significant role in overall performance of the system,the background details of which is still very sketchy in global research community.This work addresses the technical issues associated with this theology,with specific reference to formalism of a customized DIS considering real-time delay analysis.The present paper delineates the developmental paradigms of novel multi-input multioutput communication semantics for retrieving web-based information from physical devices,namely,two representative robotic sub-systems in a coherent and homogeneous mode.The developed protocol can be entrusted for use in real-time in a complete user-friendly manner.

Robotic Smart Prosthesis Arm with BCI and Kansei/Kawaii/Affective Engineering Approach.Pt I: Quantum Soft Computing Supremacy

A description of the design stage and results of the development of the conceptual structure of a robotic prosthesis arm is given.As a result,a prototype of man-made smart prosthesis on a 3D printer as well as a foundation for computational intelligence presented.The application of soft computing technology(the first step of IT)allows to extract knowledge directly from the physical signal of the electroencephalogram,as well as to form knowledge-based intelligent robust control of the lower performing level taking into account the assessment of the patient’s emotional state.The possibilities of applying quantum soft computing technologies(the second step of IT)in the processes of robust filtering of electroencephalogram signals for the formation of mental commands of robotic prosthetic arm discussed.Quantum supremacy benchmark of intelligent control simulation demonstrated.

Human Being Emotion in Cognitive Intelligent Robotic Control Pt I: Quantum/Soft Computing Approach

The article consists of two parts.Part I shows the possibility of quantum/soft computing optimizers of knowledge bases(QSCOptKB™)as the toolkit of quantum deep machine learning technology implementation in the solution’s search of intelligent cognitive control tasks applied the cognitive helmet as neurointerface.In particular case,the aim of this part is to demonstrate the possibility of classifying the mental states of a human being operator in on line with knowledge extraction from electroencephalograms based on SCOptKB™and QCOptKB™sophisticated toolkit.Application of soft computing technologies to identify objective indicators of the psychophysiological state of an examined person described.The role and necessity of applying intelligent information technologies development based on computational intelligence toolkits in the task of objective estimation of a general psychophysical state of a human being operator shown.Developed information technology examined with special(difficult in diagnostic practice)examples emotion state estimation of autism children(ASD)and dementia and background of the knowledge bases design for intelligent robot of service use is it.Application of cognitive intelligent control in navigation of autonomous robot for avoidance of obstacles demonstrated.

Intelligent Control of Mobile Robot with Redundant Manipulator & Stereovision: Quantum / Soft Computing Toolkit

The task of an intelligent control system design applying soft and quantum computational intelligence technologies discussed.An example of a control object as a mobile robot with redundant robotic manipulator and stereovision introduced.Design of robust knowledge bases is performed using a developed computational intelligence-quantum/soft computing toolkit(QC/SCOptKBTM).The knowledge base self-organization process of fuzzy homogeneous regulators through the application of end-to-end IT of quantum computing described.The coordination control between the mobile robot and redundant manipulator with stereovision based on soft computing described.The general design methodology of a generalizing control unit based on the physical laws of quantum computing(quantum information-thermodynamic trade-off of control quality distribution and knowledge base self-organization goal)is considered.The modernization of the pattern recognition system based on stereo vision technology presented.The effectiveness of the proposed methodology is demonstrated in comparison with the structures of control systems based on soft computing for unforeseen control situations with sensor system.The main objective of this article is to demonstrate the advantages of the approach based on quantum/soft computing.

School Debit Transaction Using Fingerprint Recognition System

This paper proposed a fingerprint based school debit transaction system using minutiae matching biometric technology.This biometric cashless transaction system intensely shortens the luncheon line traffic and labour force compared to conventional cash payment system.Furthermore,contrast with card cashless transaction system,fingerprint cashless transaction system with benefit that user need not carry additional identification object and remember lengthy password.The implementation of this cashless transaction system provides a more organize,reliable and efficient way to operate the school debit transaction system.

Robotic Unicycle Intelligent Robust Control Pt I: Soft Computational Intelligence Toolkit

The concept of an intelligent control system for a complex nonlinear biomechanical system of an extension cableless robotic unicycle discussed.A thermodynamic approach to study optimal control processes in complex nonlinear dynamic systems applied.The results of stochastic simulation of a fuzzy intelligent control system for various types of external/internal excitations for a dynamic,globally unstable control object-extension cableless robotic unicycle based on Soft Computing(Computational Intelligence Toolkit-SCOptKBTM)technology presented.A new approach to design an intelligent control system based on the principle of the minimum entropy production(minimum of useful resource losses)determination in the movement of the control object and the control system is developed.This determination as a fitness function in the genetic algorithm is used to achieve robust control of a robotic unicycle.An algorithm for entropy production computing and representation of their relationship with the Lyapunov function(a measure of stochastic robust stability)described.

Defect Detection in CK45 Steel Structures through C-scan Images Using Deep Learning Method

In the present paper,a method for reliable estimation of defect profile in CK45 steel structures is presented using an eddy current testing based measurement system and post-processing system based on deep learning technique.So a deep learning method is used to determine the defect characteristics in metallic structures by magnetic field C-scan images obtained by an anisotropic magneto-resistive sensor.Having designed and adjusting the deep convolution neural network and applied it to C-scan images obtained from the measurement system,the performance of deep learning method proposed is compared with conventional artificial neural network methods such as multilayer perceptron and radial basis function on a number of metallic specimens with different defects.The results confirm the superiority of the proposed method for characterizing defects compared to other classical training-oriented methods。

Machine Learning Meets the Semantic Web

Remarkable progress in research has shown the efficiency of Knowledge Graphs(KGs)in extracting valuable external knowledge in various domains.A Knowledge Graph(KG)can illustrate high-order relations that connect two objects with one or multiple related attributes.The emerging Graph Neural Networks(GNN)can extract both object characteristics and relations from KGs.This paper presents how Machine Learning(ML)meets the Semantic Web and how KGs are related to Neural Networks and Deep Learning.The paper also highlights important aspects of this area of research,discussing open issues such as the bias hidden in KGs at different levels of graph representation。

Robust PID Controller Design on Quantum Fuzzy Inference: Imperfect KB Quantum Self-Organization Effect-Quantum Supremacy Effect

The new method of robust self-organized PID controller design based on a quantum fuzzy inference algorithm is proposed.The structure and mechanism of a quantum PID controller(QPID)based on a quantum decision-making logic by using two K-gains of classical PID(with constant K-gains)controllers are investigated.Computational intelligence toolkit as a soft computing technology in learning situations is applied.Benchmark’s simulation results of intelligent robust control are demonstrated and analyzed.Quantum supremacy demonstrated.

Intelligent Robust Control of Redundant Smart Robotic Arm Pt II: Quantum Computing KB Optimizer Supremacy

This article is a continuation of the work“Intelligent robust control of redundant smart robotic arm Pt I:Soft computing KB optimizer-deep machine learning IT”.In the first part of the paper,we examined control systems with constant coefficients of the conventional PID controller(based on genetic algorithm)and intelligent control systems based on soft computing technologies.For demonstration,MatLab/Simulink models and a test benchmark of the robot manipulator demonstrated.Advantages and limitations of intelligent control systems based on soft computing technology discussed.Intelligent main element of the control system based on soft computing is a fuzzy controller with a knowledge base in it.In the first part of the article,two ways to implement fuzzy controllers showed.First way applyied one controller for all links of the manipulator and showed the best performance.However,such an implementation is not possible in complex control objects,such as a manipulator with seven degrees of freedom(7DOF).The second way use of separated control when an independent fuzzy controller controls each link.The control decomposition due to a slight decrease in the quality of management has greatly simplified the processes of creating and placing knowledge bases.In this Pt II,to eliminate the mismatch of the work of separate independent fuzzy controllers,methods for organizing coordination control based on quantum computing technologies to create robust intelligent control systems for robotic manipulators with 3DOF and 7DOF described.Quantum supremacy of developed end-to-end IT design of robust intelligent control systems demonstrated.